Prostate cancer accounts for 20 percent of all male malignancies and 11 percent of cancer deaths in men in the United States. The pathogenesis of converting prostatic intraepithelial neoplasia (PIN) to invasive carcinoma remains obscure. The long- term goal of the proposed research is to identify stage-specific gene markers and develop automated diagnosis which will facilitate early prostate cancer detection and enhance a physician's ability to make decisions on treatment. The hypotheses to be tested are (a) cell-specific, full-length cDNA libraries from prostate cells of known pathological changes from biopsied sections, cytology specimens, micro-metastasis, etc. can be generated; (b) genes which have been identified to be involved in prostatic cancer can be identified in the generated full- length cDNA libraries, and (c) Differential expression of stage- specific gene markers can be identified in different stage- specific cDNA libraries. Our immediate goal is to generate cDNA libraries from stage-specific human prostatic cancer cells obtained from histological sections; then, we will assess the quality of the cDNA libraries by confirming the full-length of a set of genes of known size and to establish the optimal condition to generate high quality cDNA libraries; we will examine differential expression of known genes of cDNA libraries generated from these stage-specific cells and identify gene markers using microarray technology as well as correlate the differentially expressed molecular markers to different stages of prostate cancer. This proposed research is worthwhile because, to this day, microarray technologies in prostate cancer have been either based on cDNA generated from xenografts and/or fluorescence in site hybridization (FISH). However, the P.I.'s laboratory has reported a newly-developed novel method of generating cell-specific full-length cDNA libraries from single cells and a laser-assisted preparation of single cells from human prostatic cancer histological slides. In this way, amplified messenger RNA libraries from a few tissue cells can provide molecular gene expression profiles at high resolution and in vivo analyses of cancerous gene expression in human prostate cancers is potentially feasible. These results may pave the way for a precise gene-chip diagnosis of stage-specific markers of human prostate cancer.